Career Summary

Biography

I received the B.E. (Hons.I.) degree in Computer Engineering in 1988, the M.E. degree in Electrical Engineering in 1992, and the Ph.D. degree in electrical engineering in 1994, all from the University of Newcastle, Australia. During 1994–1997, I was a Lecturer in the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. In 1997, I joined the University of Newcastle, where I'm currently an Associate Professor. I served as Head of School of Electrical Engineering and Computer Science (2007–2009), and Assistant Dean Research (2011–2013) for the Faculty of Engineering and Built Environment, where I'm currently Deputy Head of Faculty. My research interests are in the areas of control theory and its application to energy systems and climate.

Research ExpertiseMy research interests are in control theory and its application to energy systems and climate.

Several studies have suggested that battery storage co-located with solar photovoltaics (PV) benefits electricity distributors in maintaining system voltages within acceptable lim... [more]

Several studies have suggested that battery storage co-located with solar photovoltaics (PV) benefits electricity distributors in maintaining system voltages within acceptable limits. However, without careful coordination, these potential benefits might not be realized. In this paper we propose an optimization-based algorithm for the scheduling of residential battery storage co-located with solar PV, in the context of PV incentives such as feed-in tariffs. Our objective is to maximize the daily operational savings that accrue to customers, while penalizing large voltage swings stemming from reverse power flow and peak load. To achieve this objective we present a quadratic program (QP)-based algorithm. To complete our assessment of the customer benefit, the QP-based scheduling algorithm is applied to measured load and generation data from 145 residential customers located in an Australian distribution network. The results of this case study confirm the QP-based scheduling algorithm significantly penalizes reverse power flow and peak loads corresponding to peak time-of-use billing. In the context of feed-in tariffs, the majority of customers exhibited operational savings when QP energy-shifting.

Several studies have suggested that battery storage co-located with solar photovoltaics (PV) benefits electricity distributors in maintaining system voltages within acceptable lim... [more]

Several studies have suggested that battery storage co-located with solar photovoltaics (PV) benefits electricity distributors in maintaining system voltages within acceptable limits. However, without careful coordination, these potential benefits might not be realized. In this paper we propose an optimization-based algorithm for the scheduling of residential battery storage co-located with solar PV, in the context of PV incentives such as feed-in tariffs. Our objective is to maximize the daily operational savings that accrue to customers, while penalizing large voltage swings stemming from reverse power flow and peak load. To achieve this objective we present a quadratic program (QP)-based algorithm. To complete our assessment of the customer benefit, the QP-based scheduling algorithm is applied to measured load and generation data from 145 residential customers located in an Australian distribution network. The results of this case study confirm the QP-based scheduling algorithm significantly penalizes reverse power flow and peak loads corresponding to peak time-of-use billing. In the context of feed-in tariffs, the majority of customers exhibited operational savings when QP energy-shifting.

Algorithms and Hardware Implementation of a Processor for Low Complexity and High Performance Multi-Antenna ReceiversComputer Engineering, Faculty of Engineering and Built EnvironmentPrincipal Supervisor

2013

Computational Bayesian Methods for Communications and ControlElectrical Engineering, Faculty of Engineering and Built EnvironmentCo-Supervisor

2010

Radio Access Network Design for the Evolved UMTS NetworkElectrical Engineering, Faculty of Engineering and Built EnvironmentCo-Supervisor

2009

A Reconfigurable Prototyping System for Multiple-Input Multiple-Output CommunicationsElec&Electronic Eng&Technology, Faculty of Engineering and Built EnvironmentCo-Supervisor